Volumetric Deformation Analysis Using Mechanics-Based Data Fusion: Applications in Cardiac Motion Recovery

  • Authors:
  • Pengcheng Shi;Albert J. Sinusas;R. Todd Constable;James S. Duncan

  • Affiliations:
  • Departments of Diagnostic Radiology and Electrical Engineering, Yale University, New Haven, CT 06520;Section of Cardiology, Department of Medicine, Yale University, New Haven, CT 06520;Department of Diagnostic Radiology, Yale University, New Haven, CT 06520;Departments of Diagnostic Radiology and Electrical Engineering, Yale University, New Haven, CT 06520

  • Venue:
  • International Journal of Computer Vision
  • Year:
  • 1999

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Abstract

Non-rigid motion estimation from image sequences is essential inanalyzing and understanding the dynamic behavior of physicalobjects. One important example is the dense field motion analysis ofthe cardiac wall, which could potentially help to better understandthe physiological processes associated with heart disease and toprovide improvement in patient diagnosis and treatment. In this paper,we present a new method of estimating volumetric deformation byintegrating intrinsic instantaneous velocity data with geometricaltoken displacement information, based upon continuum mechanicsprinciples. This object-dependent approach allows the incorporationof physically meaningful constraints into the ill-posed motionrecovery problem, and the integration of the two disparate butcomplementary data sources overcomes some of the limitations of thesingle-image-source-based motion estimation approaches.